Our Services
Our team collaborated closely with Slight Insane to develop a state-of-the-art virtual try-on solution that leverages advanced augmented reality (AR) and machine learning technologies. We focused on creating an intuitive, seamless, and highly accurate virtual fitting experience that would enhance user engagement and reduce return rates.
Tech Used
Our virtual try-on feature integrates web and AI technologies, using React.js for responsive frontend, WebGL and Three.js for 3D rendering, and machine learning algorithms with TensorFlow and OpenCV for body mapping and garment simulation. Powered by Node.js, AWS, Docker, and Kubernetes, it ensures scalable, high-performance deployment.
Overview
Slight Insane, a forward-thinking fashion technology company, recognized the growing gap between online shopping convenience and the tactile experience of trying on clothes in-store. To address this, they set out to innovate with a virtual try-on solution that would bring the fitting room to customers’ screens. With rising consumer demand for personalization and confidence in online purchases, the brand aimed to create a feature-rich, interactive experience that allows users to visualize apparel in real time. The goal was to reduce product returns, improve customer satisfaction, and position Slight Insane as a pioneer in immersive e-commerce technology.
Challenges
Accurate Body Mapping: Developing an AI-powered system that precisely maps a user's body measurements in real-time, accounting for diverse body types and clothing styles.
Performance Optimization: Ensuring smooth, lag-free rendering of virtual clothing items while maintaining high-quality graphics and minimal computational load.
Realistic Clothing Simulation: Creating algorithms that accurately simulate fabric drape, movement, and how different materials interact with body movements.
Cross-Device Compatibility: Designing a solution that works seamlessly across various devices, from desktop computers to mobile smartphones, with varying camera capabilities.
Solution
Advanced Body Scanning: Developed a machine learning model using TensorFlow.js to detect body landmarks and create a 3D body model with sub-millimeter accuracy.
Real-Time Rendering: Utilized WebGL and Three.js to create high-fidelity, real-time clothing simulations that update instantaneously as users move.
Adaptive Clothing Physics: Implemented a custom physics engine that simulates fabric behavior, accounting for material properties, body movement, and garment fit.
Responsive Design: Created a responsive AR framework that adapts to different device capabilities, ensuring a consistent experience across platforms.
Results
40% Reduction in Returns: The virtual try-on feature reduced return rates by 40%, as customers were more confident in their purchases after trying on items virtually.
Increased Engagement: Customers spent more time on the website exploring new styles, resulting in a 30% increase in average session duration.
Higher Conversion Rates: The try-on feature led to a 25% increase in conversion rates as customers were more likely to make a purchase after visualizing the clothing on themselves.
Improved Customer Satisfaction: The innovative feature enhanced the overall shopping experience, leading to an improvement in customer feedback and loyalty.
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